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    Two-Stage Optimal Dispatch for Integrated Energy System with Oxy-Combustion Based on Multi-Energy Flexibility Constraints
    PENG Chuxuan, BIAN Xiaoyan, JIN Haixiang, LIN Shunfu, XU Bo, ZHAO Jian
    Journal of Shanghai Jiao Tong University    2025, 59 (9): 1281-1291.   DOI: 10.16183/j.cnki.jsjtu.2023.487
    Abstract1810)   HTML19)    PDF(pc) (2004KB)(5719)       Save

    As one of the most promising carbon capture technologies for coal-fired power plants, oxy-fuel combustion provides a new solution for improving the flexibility of the integrated energy system (IES) and reducing carbon emissions. In this paper, a two-stage optimal dispatch strategy for the integrated energy system with oxy-fuel combustion units considering the constraints of multi-energy flexibility is proposed based on the intergration of oxy-fuel combustion technology and the optimal operation of the integrated energy system. First, a model of integrated energy system with oxy-fuel combustion (Oxy-IES) is established. Then, a matrix model of multi-energy flexibility constraints for Oxy-IES is proposed to reveal the supply and demand relationship of flexibility within the system. Finally, a two-stage optimization dispatch strategy for Oxy-IES is constructed, in which the output of each unit is optimized to minimize the daily operating cost of carbon trading in the day-ahead stage, while the rapid variable load capacity of the oxy-fuel combustion unit improves the flexibility of the system in the intraday stage. The simulation results of Oxy-IES show that the proposed strategy can improve the flexibility and economy performance of the IES while reducing carbon emissions.

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    Interpretation of Chinese Guidelines for the Prevention and Management of Bronchial Asthma (2024 Edition)
    ZHOU Yan, ZHANG Min
    Journal of Diagnostics Concepts & Practice    2025, 24 (04): 415-422.   DOI: 10.16150/j.1671-2870.2025.04.008
    Abstract2074)   HTML86)    PDF(pc) (509KB)(5471)       Save

    According to the Global Burden of Disease (GBD) data for 2021, the global age-standardized prevalence of asthma is 3 340.1/100 000, with a total of about 260 million patients, a mortality rate of 5.2/100 000, and 436 000 deaths. A 2012-2015 survey conducted in China shows that the prevalence of wheezing-related asthma among people aged 20 and above is 4.2%, with a total of about 45.7 million patients. However, the diagnosis rate is only 28.8%, and the control rate is only 28.5%, far below the international level, highlighting the urgent need for better asthma management and intervention. In March 2024, the Chinese Thoracic Society (CTS) released the Guidelines for the Prevention and Management of Bronchial Asthma (2024 Edition) (hereinafter referred to as the "2024 Guidelines"). For diagnostic pathways, the 2024 Guidelines improve the diagnostic criteria for asthma, emphasizing the evidence for variable expiratory airflow (such as bronchodilator tests, provocation tests, etc.). A "presumptive diagnosis pathway" is proposed for primary care and resource-limited medical institutions to improve the diagnosis rate and avoid overtreatment. In terms of staging and classification, the concept of "clinical remission" is introduced, defined as being asymptomatic for ≥1 year without the need for systemic glucocorticoid therapy. The classification of "intermittent state" is eliminated, and asthma severity is now simplified into three levels—mild, moderate and severe—with a dynamic assessment model proposed. The assessment system newly includes a type 2 inflammatory phenotype assessment, recommending the measurement of biomarkers such as peripheral blood eosinophil count (EOS) and fractional exhaled nitric oxide (FeNO) to guide individualized treatment, while also emphasizing comorbidity screening and risk factor assessment. In terms of treatment strategies, a stepwise management approach is used for chronic persistent treatment, with inhaled corticosteroid (ICS)-formoterol recommended as the preferred reliever (Pathway 1) to reduce the risk of acute exacerbations. The management of severe asthma emphasizes the use of biological targeted drugs, such as anti-IgE and anti-interleukin (IL)-5 monoclonal antibodies, while the treatment of acute exacerbations is recommended based on the severity level. Despite the significant progress made in the 2024 Guidelines, challenges remain. Epidemiological data on asthma in China are outdated, highlighting the urgent need for nationwide surveys to reflect the latest disease burden. Diagnosis rates in primary care are low, and inflammation assessment and dynamic mana-gement are insufficient, requiring strengthened capacity building at the primary care level. Real-world data on biologics in China are limited, restricting their application in precision therapy. The application of information technology in asthma management is still at an exploratory stage, and technologies like 5G should be leveraged to enhance patient education and follow-up efficiency. In the future, asthma prevention and treatment in China need to further optimize strategies for early diagnosis and early treatment, dynamically identify inflammatory phenotypes, establish drug response prediction models, and promote AI-assisted diagnosis and treatment to achieve more precise management.

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    Renewable Energy Consumption Strategies of Power System Integrated with Electric Vehicle Clusters Based on Load Alignment and Deep Reinforcement Learning
    LIU Yanhang, QIAO Ruyu, LIANG Nan, CHEN Yu, YU Kai, WU Hanxiao
    Journal of Shanghai Jiao Tong University    2025, 59 (10): 1464-1475.   DOI: 10.16183/j.cnki.jsjtu.2023.529
    Abstract1863)   HTML15)    PDF(pc) (3345KB)(3919)       Save

    As China accelerates the construction of power systems with renewable energy as the mainstay, the large-scale integration of renewables has led to prominent issues such as wind and light curtailment. To improve the utilization of new energy consumption in power systems, this paper proposes a novel renewable energy consumption method based on load alignment and deep reinforcement learning. First, it proposes a node load line formation model based on linearized power flow calculations, which can guide adjustable loads to shift the electricity consumption period, thereby promoting the improvement of new energy consumption. Unlike the direct current (DC) power flow model, the proposed alternating current (AC) model accounts for voltage constraints and other related constraints of the power system. Compared with other AC power flow models, this model linearizes all nonlinear constraints and has lower computational costs. Then, this paper constructs a market framework for load alignment mechanism. The framework involves three main entities: independent system operators, regional power grid sellers, and electric vehicle adjustable load aggregators. It also explores the solution for load alignment incentive prices using electric vehicle clusters as adjustable loads. As the solution of the load benchmark incentive price involves a master-slave game between three entities, conventional mathematical analysis methods face high complexity. Therefore, it employs deep reinforcement learning algorithm to solve the problem. The deep reinforcement learning algorithm takes the marginal electricity price of each node as state space, the load benchmark incentive price as action space, and the cost of regional power grid sellers as feedback. The agent can find the load line incentive price that maximizes the benefits of regional power grid sellers after continuous training. Finally, the example analysis shows that the load alignment mechanism not only effectively promotes the improvement of new energy consumption level, but also enhances the interests of independent system operators, regional power grid sellers, and electric vehicle aggregators. The results further confirm that the deep reinforcement learning algorithm maximizes the benefits of regional power grid sellers.

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    A Short-Term Carbon Emission Accounting Method for Power Industry Using Electricity Data Based on a Combined Model of CNN and LightGBM
    ZENG Jincan, HE Gengsheng, LI Yaowang, DU Ershun, ZHANG Ning, ZHU Haojun
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 746-757.   DOI: 10.16183/j.cnki.jsjtu.2023.382
    Abstract3258)   HTML27)    PDF(pc) (6089KB)(3775)       Save

    The electric power industry plays a pivotal role in carbon emission control. Accurate and real-time accounting of carbon emissions in the power industry is essential for supporting the carbon reduction of the power industry. At present, the measurement of carbon emissions in the power industry relies mainly on direct measurement or the accounting methods, which often struggles to balance low measurement costs with real-time accuracy. Therefore, in this paper, the robust power data infrastructure in the power industry is leveraged and the correlation between electricity consumption and carbon emissions is explored to propose a short-term electricity-to-carbon method using machine learning methods based on historical data of electricity. This method utilizes convolutional neural networks (CNNs) for feature extraction, and light gradient boosting machine (LightGBM) for carbon emission estimation based on extracted features. Moreover, K-fold cross-validation is used in model training, with parameter optimization using grid search to enhance the generalization capability and robustness of the model. To validate the proposed method, it is compared with other machine learning models under the same data segmentation condition for daily and hourly data sets. The results indicate that the proposed model outperforms other models in both performance evaluation and the consistency between estimated and target values.

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    Detection of Roadside Vehicle Parking Violations Under Random Horizontal Camera Condition
    ZHAN Zehui, ZHONG Ming’en, YUAN Bingan, TAN Jiawei, FAN Kang
    Journal of Shanghai Jiao Tong University    2025, 59 (10): 1568-1580.   DOI: 10.16183/j.cnki.jsjtu.2023.578
    Abstract840)   HTML22)    PDF(pc) (46166KB)(3102)       Save

    Investigation and punishment of vehicle parking violations is important in urban traffic management. Considering the time-consuming and labor-intensive nature of manual law enforcement, as well as the limited scope of fixed camera monitoring and detecting, exploring more flexible and efficient automatic detection methods has a great practical significance. Thus, a cruise detection technology is proposed, which is suitable for mobile carriers requiring no stopping and can be completed in a single pass. First, a vehicle parking violation image dataset named XMUT-VPI is collected and constructed under the conditions of approximate horizontal views and random shooting angles, laying a data foundation for the research. Then, a multitask parking network (MTPN) is constructed as an encoder to extract the key element information required for stop violation judgment. With the aid of the self-designed deformable large kernel feature aggregation module (DLKA-C2f) and cross-task interaction attention mechanism (CTIAM), a highest average detection accuracy of 90.3%, a minimum average positioning error of 4.4%, and a suboptimal average segmentation intersection ratio accuracy of 78.5% are achieved. Finally, an efficient decoder is designed to further extract the skeleton features of the parking space line and fit the visible area of the main parking space, which helps match the target vehicle and analyzes the positional condition between its tire ground-touching points and the main parking space. In addition, a judgment principle is provided for three typical behaviors of illegal parking, improper parking, and standardized parking. Experimental results show that the algorithm attains a comprehensive accuracy rate of 98.1% for vehicle parking violation detections across diverse complex interference scenarios, which outperforms existing mainstream methods and can provide technical supports for fully automate road cruise management of parking violatic.

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    Transient Modeling and Characteristic Comparative Analysis of Grid-Forming VSC with and Without Current Control
    REN Xiancheng, LI Shangzhi, LI Yingbiao, HU Jiabing, XU Taishan, BAO Yanhong, WU Feng
    Journal of Shanghai Jiao Tong University    2025, 59 (7): 971-982.   DOI: 10.16183/j.cnki.jsjtu.2023.416
    Abstract2133)   HTML24)    PDF(pc) (2357KB)(2937)       Save

    As the support capacity of renewable energy generation equipment for the power grid needs enhancement, grid-forming control has attracted extensive attention, among which the virtual synchronous generator (VSG) has emerged as a key research frontier and is already being applied in engineering demonstration. Voltage source converter (VSC) with VSG as the synchronization link can be classified into voltage and current dual loop control and direct voltage control according to whether there is a current control loop in the structure. The difference in the two control structures has a significant impact on the transient characteristics of VSC. To study the difference between transient characteristics of two kinds of VSCs, the transient models are developed based on the “power excitation-internal voltage response” model, and the formation mechanism of internal voltage and transient characteristics are comparatively analyzed. Since the VSG simulates the operation characteristics of the synchronous machine, the equivalent inertia and equivalent damping of the VSC are analytically obtained at the electromechanical scale, and their transient behaviors are compared. It is found that the equivalent inertia and damping of a VSC with direct voltage control remain constant, while those of a VSC with voltage and current dual loop control exhibit time-varying characteristics and are numerically smaller than of the direct voltage control system. Finally, the validity of the theoretical analysis is confirmed by electromagnetic transient simulation.

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    An Evolutionary Game Approach to Incentive Mechanism of Vehicle-to-Grid
    PAN Yi, WANG Mingshen, MIAO Huiyu, YUAN Xiaodong, HAN Huachun
    Journal of Shanghai Jiao Tong University    2025, 59 (11): 1637-1646.   DOI: 10.16183/j.cnki.jsjtu.2023.603
    Abstract1889)   HTML20)    PDF(pc) (4079KB)(2647)       Save

    Electric vehicles (EVs) can provide significant support for the flexible operation of power systems, in which vehicle-to-grid (V2G) mode is an important way for EVs to participate in the frequency and voltage regulation of power grids. However, the commercialization of V2G has experienced slow progress to date, and the lack of an effective market operation mechanism makes it difficult for large-scale EVs to participate in the ancillary services of the grid. Therefore, a novel evolutionary game model is proposed with the participation of the electricity regulatory commission, power grid company, and EVs and the impact of the strategic choices of the three parties on the operation of the V2G market is explored to identify the subsidy and pricing mechanisms for the government to facilitate the long-term evolution of the V2G. First, replicator dynamic equations for the game are established to investigate the stability of multiple strategy equilibrium points in the three-party evolutionary game. Then, the Lyapunov stability theory is employed to analyze the stability of these equilibrium points and to determine the subsidy amount to promote V2G development. Next, a simulation analysis is conducted on the actual electricity price data from Shanghai in China, which quantitatively identified the government subsidy coefficient range and electricity price range to incentivize EV participation in the V2G model. The simulation results provide theoretical support for the electricity regulatory commission and power grid company in formulating subsidy and pricing strategies.

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    Interpretation of global stroke report data in 2025: gradient evolution and precise management of stroke burden
    TANG Chunhua, GUO Lu, ZHANG Lili
    Journal of Diagnostics Concepts & Practice    2025, 24 (05): 485-497.   DOI: 10.16150/j.1671-2870.2025.05.003
    Abstract2834)   HTML169)    PDF(pc) (777KB)(2557)       Save

    In 2021, there were 93.816 million prevalent cases of stroke worldwide [age-standardized prevalence rate(ASPR) 1 099/100 000], with 11.946 million new cases in that year [age-standardized incidence rate(ASIR) 142/100 000]. Among these new cases, ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH) accounted for 65.3% (7.804 million), 28.8% (3.444 million), and 5.8% (0.697 million), respectively. In the same year, stroke caused 7.253 million deaths, accounting for 10.7% of all global deaths. Deaths caused by IS, ICH, and SAH accounted for 49.5% (3.591 million), 45.6% (3.308 million), and 4.9% (353 000), respectively. In 2021, stroke remained the second leading cause of death worldwide, with its core disease burden indicator — disability-adjusted life years (DALYs) — exceeding 160 million, ranking third among all global total disease burdens. In terms of economic burden, the global direct medical costs and productivity losses caused by stroke reached 890 billion USD in 2021 (accounting for 0.66% of the global GDP), and are projected to exceed 1.8 trillion USD by 2050 if the current growth rate persists. The global stroke burden exhibits a dual trend of "increasing absolute numbers but decreasing age-standardized rates". Low- and middle-income countries bear most of the disease burden, and the incidence of stroke shows a coexistence of younger and older onset. In terms of risk factors, the burden of traditional behavior-related risks has decreased, while the attributable burden of metabolic and climate-related risks is rapidly increasing. China bears the heaviest stroke burden globally, characterized by a “four-high” pattern of “high incidence, high prevalence, medium-to-high mortality, and medium-to-high DALYs”, with significant urban-rural and regional disparities. This condition results from the combined effects of accelerated population aging and continuously increasing exposure to risk factors. In 2021, there were 26.335 million prevalent cases in China, with ASPR of 1 301.4/100 000. In 2021, there were 4.09 million new stroke cases in China (ASIR 204.8/100 000), accounting for 34.2% of all new global cases—far exceeding China's proportion of the world's population (about 20%). IS accounted for 67.8% [2.772 million cases, age-standardized incidence rate (ASIR) 135.8/100 000], and ICH accounted for 28.7% (1.173 million cases, ASIR 61.2/100 000). The annual total economic burden of stroke in China has exceeded 400 billion RMB, with its proportion in the national healthcare expenditure continuing to increase. Direct medical costs account for about 60%, while indirect costs (including productivity losses and caregiving expenses) account for 40%, imposing a dual pressure on both society and families. To address this challenge, a stratified precision prevention and control system centered on the coordination of "policy-healthcare-society" should be established, covering primordial, primary, and secondary prevention levels. Emphasis should be placed on cross-sector collaboration, data-driven approaches, and international experience sharing to achieve effective control of the stroke burden and promote global health equity.

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    Cascade Sliding Mode Decoupling Control of Coupled Inductor Single-Input Dual-Output Buck Converter Based on Super-Twisting Extend State Observer
    HUANG JinFeng, ZHANG Qian
    Journal of Shanghai Jiao Tong University    2025, 59 (5): 592-604.   DOI: 10.16183/j.cnki.jsjtu.2023.349
    Abstract1932)   HTML4)    PDF(pc) (4220KB)(2466)       Save

    To address the coupling effect between the output branches of the coupled inductor single-input dual-output (CI-SIDO) Buck converter, which leads to the cross-influence and thus affects the dynamic performance of the system, a cascaded sliding mode decoupling control strategy based on the super-twisting extend state observer (ST-ESO) is proposed. First, a state-space averaging model of the CI-SIDO Buck converter is established. Then, the coupling terms, internal perturbations, and unmodeled parts in the inner and outer loops of the converter are estimated by using the ST-ESO with a fast-convergence property, which are regarded as the total perturbations in the inner and outer loops. Next, the total perturbation in the inner and outer loops is compensated by using a super-twisting sliding mode controller to achieve the decoupling of the system and ensure the robustness of the system and the stability of the output voltage. Furthermore, the stability of the super-twisting extend state observer and super-twisting sliding mode controller is analyzed using the Lyapunov theory, providing theoretical verification of the feasibility of the control strategy. Finally, the proposed control strategy is experimentally validated on the experimental platform. The results show that the proposed control strategy realizes the decoupling of the system, suppresses the cross-influence and improves the dynamic performance of the system.

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    Interpretation of key points in 2025 KDIGO Clinical Practice Guideline for the Evaluation,Management,and Treatment of Autosomal Dominant Polycystic Kidney Disease
    WU Shuangcheng, YU Shengqiang
    Journal of Diagnostics Concepts & Practice    2025, 24 (03): 255-262.   DOI: 10.16150/j.1671-2870.2025.03.003
    Abstract890)   HTML23)    PDF(pc) (1343KB)(2319)       Save

    Autosomal dominant polycystic kidney disease (ADPKD) is one of the most common hereditary renal cystic disorders and a major cause of end-stage renal disease requiring renal replacement therapy. In February 2025, Kidney Disease: Improving Global Outcomes (KDIGO) released the first clinical practice guideline specifically for ADPKD entitled "KDIGO Clinical Practice Guideline for the Evaluation, Management, and Treatment of Autosomal Dominant Polycystic Kidney Disease". The guideline comprises 10 chapters covering nomenclature, diagnosis, prognosis, and prevalence of ADPKD; renal manifestations; management and progression of chronic kidney disease, renal failure, and renal replacement therapy; treatments to delay renal disease progression; polycystic liver disease; intracranial aneurysms and other extrarenal manifestations; lifestyle and psychosocial considerations; pregnancy and reproductive problems; pediatric problems; and approaches to ADPKD patient management. It highlights early diagnosis, risk stratification, integrated management, and application of the new drug tolvaptan. Additionally, the guideline introduces a new nomenclature system based on pathogenic genes for the first time, along with more stringent blood pressure management plans. By integrating guideline highlights, evidence-based medicine, and China's clinical practice, this study interprets two key clinical issues in the updated guideline: "early diagnosis and risk stratification of ADPKD" and "treatment and daily management of kidney-related symptoms." A thorough analysis of the guideline's implications and limitations is conducted, aiming to promote standardized diagnosis and therapy for ADPKD.

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    Capacity Planning and Operational Optimization for Low-Carbon Data Center Integrated Energy System Considering Exergy Efficiency
    LIN Jiayu, HAN Juntao, WANG Yongzhen, HAN Kai, HAN Yibo, LI Jian
    Journal of Shanghai Jiao Tong University    2025, 59 (9): 1327-1337.   DOI: 10.16183/j.cnki.jsjtu.2023.528
    Abstract2225)   HTML10)    PDF(pc) (3820KB)(2287)       Save

    With the rapid development of the digital economy, the energy consumption and carbon emissions of data centers (DCs) have significantly increased. In recent years, the construction of data center integrated energy systems (DC-IES) has emerged as one of the critical trends in energy conservation and emission reduction for DCs under the global net-zero emission initiative. To support the planning and construction of low-carbon DC-IES, this paper proposes a multi-objective optimization model for capacity allocation and operational planning of DC-IES, integrating energy and economic considerations with a focus on low-carbon performance. Based on the “quality” analysis method of exergy from the second law of thermodynamics, the model proposed comprehensively accounts for the dynamic exergy efficient characteristics of energy conversion devices under varying load conditions, revealing the energy flow distribution characteristics of DC-IES under different objectives. The computational results indicate that compared with the optimization scheme assuming constant equipment efficiency, the scheme considering dynamic equipment efficiency reduces energy loss rate, economic cost, and carbon emissions by 2.6%, 1.9%, and 4.8%, respectively, demonstrating clear advantages. Moreover, compared with the economically optimal scheme, the multi-objective optimization scheme significantly reduces carbon emissions and energy loss rate of the DC-IES by 22.72% and 20.73%, respectively. Furthermore, compared to the scheme scenarios with the minimum exergy loss rate and lowest carbon emissions, the multi-objective optimization scheme reduces economic costs by 54.54% and 60.78%, respectively. Compared with the scheme relying solely on grid electricity supply, the multi-objective optimization scheme that regards the DC as an integrated energy system can reduce carbon emissions by 40.97%.

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    Reactive Power-Voltage Droop Gain Online Tuning Method of Photovoltaic Inverters for Improvement of Stable Output Power Capability in Weak Grids
    WANG Yuyang, ZHANG Chen, ZHANG Yu, WANG Yiming, XU Po, CAI Xu
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 845-856.   DOI: 10.16183/j.cnki.jsjtu.2023.353
    Abstract2634)   HTML14)    PDF(pc) (7800KB)(2236)       Save

    The active power output capability and small signal stability in weak grids are key factors that limit stable photovoltaic (PV) power generation. To improve stably generating PV power in weak grids, an adaptive control method for PV inverters based on online tuning of the reactive power-voltage (Q-V) droop gain is proposed. First, to ensure active power output capability in weak grids, a “first optimization” method for the Q-V droop gain is proposed, considering voltage and current constraints. Then, to address stability constraints in weak grids, impedance modeling and stability analysis of the PV inverter system are conducted. A mapping relationship between the “parameter-weakest pole” is established with the weakest pole of the closed-loop system as a stability constraint based on the artificial neural network. A “second adjustment” method for the Q-V droop gain is developed at stably generating active power. Combined with the extended Kalman-filter-based grid impedance estimation, the proposed Q-V droop gain adaptive tuning method is realized. The effectiveness of the proposed adaptive control method is validated on the Modeling Tech real-time simulation platform.

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    Control Strategy for Improving Active Frequency Support Capability of Offshore Wind Farm
    LI Yibo, ZHOU Qian, ZHU Dandan, JIANG Yafeng, WU Qiuwei, CHEN Jian
    Journal of Shanghai Jiao Tong University    2025, 59 (10): 1442-1450.   DOI: 10.16183/j.cnki.jsjtu.2023.581
    Abstract2435)   HTML7)    PDF(pc) (1522KB)(2060)       Save

    In low frequency alternating current (AC) transmission systems, offshore wind farm is unable to respond to changes in onshore grid frequency in a timely manner due to frequency decoupling and signal transmission delays between the offshore wind power system and the onshore AC system. To address this issue, a control strategy is proposed to improve the active frequency support capability of offshore wind farms by combining the system inertia. In terms of frequency signaling, an additional frequency sag controller is designed based on the V/f control strategy of the low-frequency-side structure network of modular multilevel matrix converter (M3C), combining with the system inertia. The frequency coupling link between the M3C net side and the low-frequency side is established to realize the real-time transmission of frequency information between the two sides. In terms of frequency support, when the system is disturbed to generate frequency deviation, the offshore wind turbine can adjust the power command value through additional droop control, thereby providing frequency support for the system. Finally, the effectiveness of the proposed coordinated control strategy is verified in MATLAB/Simulink by the simulation of load change and three-phase AC short circuit fault.

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    From Kill Chain to Kill Web: A Survey on Modeling, Evaluation, and Optimization
    WANG Chaochen, JIANG Hongru, WANG Buli, XIA Qiaowei, ZHANG Xianchun
    Air & Space Defense    2025, 8 (4): 1-8.  
    Abstract2950)      PDF(pc) (992KB)(1802)       Save
    This paper comprehensively and systematically analyzed the theoretical evolution, model construction, effectiveness evaluation, and optimization methodologies of kill chains and webs. First, the fundamental distinctions between kill chains and kill webs were introduced via conceptual comparative analysis. Then, from the perspective of four key modeling challenges: structured information representation, cooperative system optimization, dynamic adaptability, and intelligent decision-making, the construction mechanisms and technological breakthroughs of various models were investigated. Quantitative evaluation methods for key dimensions, including survivability, resilience, and node importance, were summarized. Following this, strategies for dynamic reconstruction optimization and multi-objective conflict resolution were studied. Finally, future development trends of kill chains and kill webs were projected.
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    Analysis of global trends and current status of diagnosis and treatment of inflammatory bowel diseas
    YANG Cuiping, CHEN Ping
    Journal of Diagnostics Concepts & Practice    2025, 24 (04): 373-382.   DOI: 10.16150/j.1671-2870.2025.04.003
    Abstract2400)   HTML161)    PDF(pc) (571KB)(1795)       Save

    Inflammatory bowel disease (IBD) is a group of chronic, recurrent, nonspecific inflammatory intestinal disorders of unknown etiology, primarily comprising ulcerative colitis (UC) and Crohn's disease (CD). Over the past 30 years, IBD has transitioned from a traditional "Western disease" to a truly global disease. The prevalence of IBD in North America and Europe has stabilized at 0.5%-1.0%, while newly industrialized countries in Asia, Latin America, and Africa are experiencing a 5 to 10-fold surge in IBD incidence. It is projected that the total number of IBD patients in Asia will exceed 4 million by 2035. From 1990 to 2019, the number of IBD patients in China increased from 133 000 to 484 000 in males and from 107 000 to 427 000 in females. The age-standardized incidence of IBD in Chinese males and females increased from 1.72/100 000 and 1.20/100 000 to 3.35/100 000 and 2.65/100 000, respectively. By 2030, the number of IBD patients in China is projected to exceed 1 million. In terms of diagnosis, magnetic resonance enterography (MRE), computed tomography enterography (CTE), and video capsule endoscopy (VCE) have significantly improved the visualization of small bowel lesions. Fecal calprotectin (FC) (optimal threshold of 152 μg/g) can predict relapse, with a sensitivity of 72% and a specificity of 74%. Anti-neutrophil cytoplasmic antibody (ANCA) and anti-saccharomyces cerevisiae antibody (ASCA) can also provide a non-invasive basis for differentiating UC and CD. The multidisciplinary team (MDT) model has improved the diagnosis rate of difficult cases by 20%. In the field of treatment, conventional therapies including 5-aminosalicylic acid, corticosteroids, and immunomodulators remain the foundation. However, biologics and small molecule targeted drugs such as anti-tumor necrosis factor-α agents, anti-interleukin (IL)-12/23 agents, and Janus kinase inhibitors have become the core treatments for patients with moderate to severe IBD, achieving induction remission rates of 50%-70%. Endoscopic dilation, endoscopic mucosal resection, endoscopic submucosal dissection, or laparoscopic surgery combined with enhanced recovery after surgery can significantly reduce trauma. Exclusive enteral nutrition and probiotic interventions can achieve a remission rate of 60%-70% in pediatric CD patients. However, the accessibility of biologics in primary hospitals in China is less than 30%, and the implementation rate of enhanced recovery after surgery is below 40%, indica-ting a significant gap compared with Europe and America. In the future, a national IBD registry system should be established, and research on early diagnostic models based on artificial intelligence (AI) and pharmacoeconomics should be conducted to achieve precise prevention and treatment of IBD and alleviate the societal burden of the disease.

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    A Fault Diagnosis Method for Wind Turbines Based on Zero-Shot Learning
    PAN Meiqi, HE Xing
    Journal of Shanghai Jiao Tong University    2025, 59 (5): 561-568.   DOI: 10.16183/j.cnki.jsjtu.2023.375
    Abstract2570)   HTML21)    PDF(pc) (1123KB)(1721)       Save

    In engineering practice, wind turbine fault diagnosis encounters situations where the fault category in the training data is different from the actual one. To diagnose unknown wind turbine faults, it is necessary to transfer the fault feature information learned during training to the unknown fault category. Unlike traditional methods that directly establish mapping between fault samples and fault categories, a zero-shot learning (ZSL) method for wind turbine fault diagnosis based on fault attributes is proposed to enable fault feature migration. A fault attribute matrix is established by describing the attributes of each fault, which is embedded into the fault sample space and fault category space. Then, a fault attribute learner is developed based on convolutional neural network (CNN), and a fault classifier is established based on Euclidean distance, forming the diagnosis process where fault attributes are predicted from fault samples and then classified. Finally, the effectiveness and superiority of the proposed fault diagnosis method are validated by comparing it with other zero-shot learning methods.

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    An Improved Multi-Objective Evolutionary Algorithm for Grid Map Path Planning
    DONG Dejin, WANG Changcheng, CAI Yunze
    Journal of Shanghai Jiao Tong University    2025, 59 (10): 1558-1567.   DOI: 10.16183/j.cnki.jsjtu.2024.032
    Abstract743)   HTML15)    PDF(pc) (4493KB)(1676)       Save

    Multi-objective path planning on large-scale grid maps is characterized by a large number of nodes and multiple targets. Existing algorithms struggle to balance the speed and quality of solving the Pareto front (PF). Therefore, studying efficient optimization algorithms based on the PF has certain theoretical significance. First, a weighted graph modeling method based on cost vector is proposed, and optimization algorithms for solving large-scale problems are studied accordingly, which significantly saves time and costs compared with graph search algorithms. Then, to address the issue of low quality of the PF solutions, an improved multi-objective evolutionary algorithm is proposed, which includes a new initialization strategy. Individual and environment selection strategies are designed based on the concepts of angle and shift-based density. These improvements take both population diversity and convergence into account, thereby improving the solving efficiency. Finally, comparative simulation experiments are conducted to verify the effectiveness of the improved algorithm.

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    Optimization of Installed Wind Power Capacity Considering Dynamic Frequency Constraints and Multiple Uncertainties
    YE Jing, HE Jiehui, ZHANG Lei, CAI Junwen, LIN Yuqi, XIE Jihao
    Journal of Shanghai Jiao Tong University    2025, 59 (9): 1292-1303.   DOI: 10.16183/j.cnki.jsjtu.2023.474
    Abstract1858)   HTML4)    PDF(pc) (1708KB)(1594)       Save

    As the installed capacity of wind power continues to increase, the frequency security of new power system becomes increasingly significant. To guarantee the frequency security of the system, improve the frequency regulation capability of the system, and determine an optimal wind power installed capacity, a wind power installed capacity optimization model considering dynamic frequency constraints as well as load-side inertia is proposed. First, the dynamic frequency response model with load-side inertia is derived. Then, fuzzy opportunity constraints are introduced considering the uncertainty of wind power, load, and load-side inertia. Taking into account the dynamic frequency constraints, the model incorporates multiple uncertainty fuzzy opportunity constraints, in which the uncertainty constraints are clearly converted into equivalence classes. Finally, to address the dynamic frequency-constrained nonlinear characteristic, the optimization problem is partitioned into a main problem and sub-problems for solution. The validity and feasibility of the proposed model are validated by using an improved 10-machine system.

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    Multi-Objective Optimization Design of Micro-Site Selection of Complex Terrain Wind Farms Assisted by Proxy Model
    LIU Jiahui, WANG Cong, ZHANG Hongli, MA Ping, LI Xinkai, DONG Yingchao
    Journal of Shanghai Jiao Tong University    2025, 59 (9): 1315-1326.   DOI: 10.16183/j.cnki.jsjtu.2023.486
    Abstract2319)   HTML12)    PDF(pc) (5456KB)(1552)       Save

    To tackle the challenges of high difficulty and time-consuming micro-site optimization of wind farms in complex terrains, a multi-objective optimization method for micro-site selection is proposed, assisted by proxy model. First, considering the geographical features of complex terrains with significent undulations, the ruggedness index is calculated and the ground flatness is numerically quantified, constraining the points with excessive ruggedness. Then, a mathematical model for three-dimensional windy downward wake superposition calculation of power generation is established, a three-dimensional terrain collector line topology optimization agent model is constructed, and the prediction accuracy of the proxy model is verified, demonstrating the ability to replace numerous calculations in collector line topology optimization and effectively improving the computing efficiency. Finally, taking a real complex terrain wind farm in Xinjiang Uygur Autonomous Region, China as an example, multi-objective micro-site selection of complex terrain wind farm is realized, and the results are compared with those obtained through the single-objective optimization. The simulation results show that the multi-objective discrete state transfer algorithm assisted by the proxy model can reduce the total cable laying length, decrease the construction costs, and provide more feasible layout schemes while optimizing the annual power generation.

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    Coordinated Day-Ahead Scheduling and Real-Time Dispatch of a Wind-Thermal-Storage Energy Base Considering Flexibility Interval
    YANG Yinguo, FENG Yinying, WEI Wei, XIE Pingping, CHEN Yue
    Journal of Shanghai Jiao Tong University    2025, 59 (9): 1270-1280.   DOI: 10.16183/j.cnki.jsjtu.2023.509
    Abstract2352)   HTML6)    PDF(pc) (1483KB)(1453)       Save

    Large-scale new energy bases in desert, Gobi, and arid regions are key components of new-type power systems in China. Considering factors such as construction cost and carbon emissions, the capacities of thermal power and energy storage in these bases are limited, resulting in constrained flexibility. Consequently, the scheduling and operation of these large bases face significant challenges. This paper proposes a coordinated day-ahead and real-time scheduling method for wind-thermal-storage integrated bases. In the day-ahead stage, the startup/shutdown plans and adjustable output ranges of thermal units are determined based on a rough prediction of wind power. Then, it constructs a wind power accommodation interval based on the adjustable range of thermal power output and the operational constraints of energy storage. In the real-time stage, dispatch strategies are generated using a quantile-based rule according to current wind and solar power output, eliminating the need for high-precision forecasts. It is further demonstrated that the dispatch strategies generated by the quantile rule inherently satisfy system operational constraints. The case study validates the effectiveness of the proposed method for wind-thermal-storage systems. The results demonstrate that the proposed method, which does not rely on point prediction, outperforms rolling optimization methods when the three-step prediction error exceeds 10%. Moreover, the performance of operational scheduling can be improved by enhancing the accuracy of day-ahead or intraday short-term forecasts. The proposed method provides valuable reference for the operation of large-scale new energy bases.

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    Physics-Informed Fast Transient Stability Assessment of Non-Fixed Length in Power Systems
    LI Xiang, CHEN Siyuan, ZHANG Jun, KE Deping, GAO Jiemai, YANG Huanhuan
    Journal of Shanghai Jiao Tong University    2025, 59 (7): 962-970.   DOI: 10.16183/j.cnki.jsjtu.2023.452
    Abstract2457)   HTML7)    PDF(pc) (1706KB)(1419)       Save

    Against the backdrop of “dual carbon” goals, the construction of a new power system with new energy as the main component is the main direction and key way for the transformation and upgrading of the power industry. Research into fast and accurate evaluation of transient power angle stability in the context of new power systems is of great significance. To address this, a new transient power angle stability evaluation method is proposed for power systems with grid-forming new energy based on the physics-informed sequence-to-sequence (PI-seq2seq) neural networks and cascaded convolutional neural networks models. First, the PI-seq2seq network structure is used to predict the future power angle trajectory, and a loss function with physical loss terms is constructed to guide the model training process, which avoids the long-duration time-domain simulation to ensure fast transient evaluation. Then, predicted power angle trajectory is taken as input by the cascade convolutional neural networks to evaluate the transient stability and its confidence level. A threshold judgment mechanism for the evaluation confidence level is configured to realize the transient stability judgment of the non-fixed evaluation length, which overcomes the impact of the fixed power angle curve length on the evaluation results. Finally, the method proposed is verified in the Kundur system, and the simulation results show that it has obtained satisfactory results in both the power angle curve prediction and the stability evaluation.

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    Oscillatory Stability Assessment of Renewable Power Systems Based on Frequency-Domain Modal Analysis
    GAO Lei, MA Junchao, LÜ Jing, LIU Jianing, WANG Chenxu, CAI Xu
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 821-835.   DOI: 10.16183/j.cnki.jsjtu.2023.358
    Abstract2439)   HTML10)    PDF(pc) (4521KB)(1378)       Save

    The increasing penetration of the renewable energy has increased the risks of sub/super synchronous oscillations in power systems. Therefore, it is critical to accurately evaluate the oscillatory stability of renewable power systems ensuring the safe and stable operation of the systems. In this paper, a method for evaluating the oscillatory stability of renewable power systems based on frequency-domain modal analysis is investigated. First, the frequency-domain impedance or admittance models of key equipment and stations are established, including the renewable power generators and stations, transmission lines, synchronous generators, transformers, etc. Next, a system-level frequency-domain network model is constructed based on the actual system topology. Then, the oscillatory stability of the renewable power system is evaluated by solving the zeros of the determinant of the loop impedance matrix or the node admittance matrix of the system. The weak points of the system are identified using the participated matrix of the weak oscillation mode, which provides reference for implementation of oscillation suppression measures. Taking the practical renewable power system in East China as an example, the oscillatory stability of the system considering the varying access capacity of renewables under different grid operating conditions is assessed using the frequency-domain modal analysis method. Finally, the time-domain simulation model of the actual renewable power system is built in PSCAD/EMTDC to verify the theoretical analysis.

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    Fast Prediction for Roll Motion of a Damaged Ship Based on SVR
    LIU Han, SU Yan, ZHANG Guoqiang
    Journal of Shanghai Jiao Tong University    2025, 59 (7): 1041-1049.   DOI: 10.16183/j.cnki.jsjtu.2023.431
    Abstract504)   HTML4)    PDF(pc) (5899KB)(1375)       Save

    ANSYS-AQWA is applied to analyze the rolling motion response of the damaged ship DTMB5415 under various working conditions. The results are compared with those in exiting literature to validate the practicality of the hydrodynamic model. Additionly, the rolling motion response database for the damaged ship is constructed. The support vector regression (SVR) algorithm is used to model the rolling motion database for identification, exploring the relationship between the operating condition factors and coefficients in the equation of roll motion. Finally, a fast prediction model for rolling motion is constructed and validated, offering a significant improvement in the prediction efficiency compared with traditional computational fluid dynamics models.

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    A Multiscale Simulation of Surface Discharge and Discharge Signals in SF6
    ZHOU Lubo, ZHANG Zhaoqi, WANG Dong, SONG Hui
    Journal of Shanghai Jiao Tong University    2025, 59 (9): 1397-1406.   DOI: 10.16183/j.cnki.jsjtu.2023.525
    Abstract1274)   HTML9)    PDF(pc) (7214KB)(1348)       Save

    Surface discharge is a common type of discharge occurring in gas-insulated switchgear equipment, of which the microscopic process remains unclear. Additionly, there is a lack of theoretical correlation between the microscopic process of partial discharge due to defects and the macroscopic detection signals. First, the surface discharge process in SF6 is simulated based on a fluid-chemical simulation model, revealing the variation patterns of charged particle concentration and surface streamer velocity. Then, taking the current pulse generated in the microscopic discharges as excitation sources, the discharge signals resulting from the surface discharges are simulated based on the finite integral method, establishing a correspondance between the microscopic partial discharge process and the detectable discharge signals. Compared with the conventional Gaussian excitation source, the time-domain waveforms of electromagnetic signals obtained from the microscopic discharge simulation more chosely matches to realistic conditions. These findings effectively supplement existing researches on the microscopic mechanisms of partial discharge signals, laying a foundation for the insulation state evaluation based on the discharge signal analysis.

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    Design Methods for Power Secondary System Simulation in New Power Systems
    HE Ruiwen, LU Jialiang, YANG Changxin, PENG Hao, MOHAMMAD Shahidehpour
    Journal of Shanghai Jiao Tong University    2025, 59 (10): 1419-1430.   DOI: 10.16183/j.cnki.jsjtu.2023.541
    Abstract2043)   HTML15)    PDF(pc) (3327KB)(1327)       Save

    Under the new situation, there is an urgent need to model and simulate the power secondary system which highly shares information and implements real-time decision-making, in line with the modeling and simulation requirements of new power systems. In this paper, design methods are proposed for the first time to achieve simulation of power secondary systems by correlating the operating status of the power primary system. The smart substation secondary system with complex functional descriptions is taken as the research object. First, an interrelated simulation method for power primary and secondary systems is proposed, and its simulation implementation framework, data interaction method, and data synchronization management are explained, which enables the actual electrical quantity data of the primary system to be transmitted to the secondary side, solving the problem of data source in the secondary system simulation. Then, a simulation design method for the power secondary system is proposed, incorporating system-level interaction design, component-level class design, and module-level state design based on the object-oriented unified modeling language (UML). Thus, the entire process of transmission, interaction, processing, and conversion of electrical quantity data in the secondary system can be analyzed. Finally, to validate the effectiveness of the proposed method, a case study is conducted using a short-circuit fault scenario at the 110 kV side outlet of the 220/110/10 kV main transformer bay, in conjunction with a differential protection scheme.

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    Precise Foot Feature Point Localization and Automatic Parameters Measurement
    JI Mian, LIN Yanping, WANG Dongmei, CHEN Li, MA Xin
    Journal of Shanghai Jiao Tong University    2025, 59 (5): 703-710.   DOI: 10.16183/j.cnki.jsjtu.2023.397
    Abstract1712)   HTML11)    PDF(pc) (11865KB)(1309)       Save

    In order to quickly obtain foot parameters and quantify the degree of foot deformation, an algorithm that can accurately locate foot feature points and automatically calculate foot parameters is proposed. First, a total of 93 patients participate and their foot models are obtained using the UPOD laser scanner. Then, the random sampling consensus algorithm and principal component analysis are used to align the foot coordinate system. The algorithm utilizes foot features to identify and locate feature points, enabling the parameter calculation of length, angle, and girth. The accuracy, repeatability, and consistency of the measurements are evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), interclass correlation coefficient (ICC), and Bland-Altman plots. The MAE of foot length and width is less than 2 mm, and for ball girth, instep girth, and heel girth, it is less than 4 mm. The MAPE is less than 2%, and the ICCs for the three replicates exceed 0.99. More than 95% of the scattered points in the Bland-Altman plots are within the consistency boundary. The results show that the proposed algorithm can automatically align the coordinate system, accurately locate feature points, and accurately measure foot parameters in the standing posture. The measurement accuracy meets clinical needs with high accuracy and reliability. The findings provide valuable data support for foot classification, intelligent assistive device adaptation, and personalized assistive device design, showing important clinical application potential.

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    Research on Construction Method of Digital-Intelligent Parallel Battlefield for Air Defense and Anti-Missile Based on Digital Twin
    WANG Gang, YANG Ke, QUAN Wen, GUO Xiangke, ZHAO Xiaoru
    Air & Space Defense    2025, 8 (3): 1-13.  
    Abstract2723)      PDF(pc) (1209KB)(1305)       Save
    The establishment of a digital parallel battlefield that integrates the functions of "research, combat, testing, practical operation, and training" serves as an effective and essential supporting measure for enhancing combat command and joint training capabilities, which address future intelligent high-end warfare among major powers. In the air defense and anti-missile realm, constructing a digital parallel battlefield faces several formidable challenges, including configuring complex scenarios, facilitating interactions between virtual and real forces, and simulating combat behaviours. To tackle these issues, the paper employed a digital twin modelling approach grounded in Model-Based Systems Engineering (MBSE) to enable the precise configuration of complex scenarios. Based on the Live-Virtual-Constructive (LVC) concept, a distributed simulation architecture combining virtual and real elements was established to realise seamless virtual-real interactions and efficient coordination. In addition, an Agent modelling methodology based on data/rules dual-driven was introduced to simulate intelligent combat behaviours in air defense and anti-missile operations. A multi-branch simulation deduction and auxiliary decision-making framework tailored for the parallel battlefield was constructed, achieving the organic integration of situation analysis, plan formulation, and evaluation for optimal selection. The system development was accomplished by applying the software-defined method, enabling dynamic scheduling of system resources, flexible reconfiguration, and agile deployment. The research results indicate that the newly developed digital-intelligent parallel battlefield for air defense and anti-missile, constructed by the concept of the digital twin, provides robust support for simulation applications across multiple scenarios, including equipment testing, combat experiments, joint training, and command decision-making within the domain of air defense and anti-missile.
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    A Review of Optimal Allocation and Operation of Energy Storage System for Peak Shaving and Frequency Regulation in New Type Power Systems
    FENG Mengyuan, WEN Shuli, SHI Shanshan, WANG Haojing, ZHU Miao, YANG Wen
    Journal of Shanghai Jiao Tong University    2026, 60 (1): 1-18.   DOI: 10.16183/j.cnki.jsjtu.2024.128
    Abstract1837)   HTML31)    PDF(pc) (3194KB)(1303)       Save

    To achieve China’s “dual carbon” goal, integrating large-scale renewable energy into power grids has become an irreversible trend. With the continuous increase in the use of renewable energy, the wind and solar power integration poses critical challenges to the stable operation of the power system. With the perfect dynamic response of active and reactive power, energy storage system can smooth power fluctuations caused by intermittent and uncertain renewable energy, which is conducive to promoting the access of large-scale new energy, realizing the smooth load regulation, and improving the interactive friendliness of the power grid. First, starting from the development of energy storage technology, this paper introduces the domestic and foreign research status of energy storage participating in the auxiliary service market of power peak regulation and frequency modulation. Then, it conducts a comprehensive review on the optimization configuration of energy storage systems taking into account peak shaving and frequency regulation requirements, analyzing from two perspectives: single-type setup and hybrid energy storage. Additionally, it summarizes the solving algorithms for the optimal configuration of energy storage systems. Afterwards, it proposes a grid-friendly new power system based on energy storage participation, and elaborates on collaborative scheduling methods and control strategies in multiple time scales and multiple regions from the perspective of collaborative operation. Finally, it provides an outlook on the future research direction of energy storage from four aspects, which are shared cloud energy storage, numerical intelligent aggregation modeling,intelligent and adaptive control technology, and improving multi-regional cooperation and standardization policy mechanism.

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    Unit Commitment Optimization Model Considering Impact of Multiple Operating Conditions on Unit Life Loss
    LUO Yifu, HU Qinran, QIAN Tao, CHEN Tao, ZHANG Yuanshi, ZHANG Fei, WANG Qi
    Journal of Shanghai Jiao Tong University    2025, 59 (6): 768-779.   DOI: 10.16183/j.cnki.jsjtu.2023.401
    Abstract2514)   HTML11)    PDF(pc) (3746KB)(1251)       Save

    Thermal power units face a dilemma of accelerated lifespan degradation and extended service duration. On one hand, large-scale integration of new energy sources has increased peak shaving conditions and accelerated losses of the units. On the other hand, service units will reach designed lifespan before carbon neutrality is achieved, while flexible operation of the power system necessitates extending their service life of units. Therefore, it is of great significance to consider the losses caused by varicus operating conditions on the lifespan of the unit and optimize the operating structure of the unit in scheduling simulation for unit longevity and carbon reduction efforts. To make unit life losses in theoretical research more practical, the traditional model that averages the losses in deep peak shaving conditions has been discarded. Instead, new judgment criteria for conventional and various special operating conditions of thermal power units are established. The lifespan loss cost of the unit is integrated into the operating objective function and the corresponding constraint conditions are modified. Finally, a unit commitment model considering the multi-operating condition lifespan losses of thermal power units is constructed. Example simulations indicate that the conventional model underestimates the actual loss cost of the units. In constrast, the proposed model can not only reduce the operating cost and unit life loss by considering the lifespan impacts of multi-operating conditions, but also enhance the peak shaving capacity of thermal power units and promote wind power consumption.

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    Line Transmission Constraints Effectiveness Patterns and Similarity Mining Methods in Large-Scale Power Grid Unit Commitment
    ZHENG Yuxi, ZENG Long, LIU Jianzhe, CUI Yiyang, ZHU Hong, CAO Liang, SU Yun, WEI Lei
    Journal of Shanghai Jiao Tong University    2025, 59 (9): 1260-1269.   DOI: 10.16183/j.cnki.jsjtu.2023.550
    Abstract2012)   HTML8)    PDF(pc) (1538KB)(1165)       Save

    To address the challenge of effectively filtering constraints in the unit commitment problem constrained by large-scale line transmission networks, this paper reviews the operating principles of line constraints in both transient and steady states. An effective filtering method based on load similarity mining is proposed to eliminate redundant transmission constraints and reduce the complexity of the problem. Distance functions are developed to measure the similarity of historical load data according to the influence of different nodes on line flows. Based on the similarity analysis, typical power load scenarios are clustered, and effective line constraints are identified according to their operational significance. In addition, a pre-filtering strategy is applied to system states in which line statuses remain unchanged over time, thereby reducing the computational burden during the mining process. Simulations conducted on the IEEE 118 and Case2746wop systems validate the effectiveness of the proposed method, showing that the proposed method efficiently eliminates 99% of ineffective line constraints, and reduces solving time by over 80% compared to existing approaches.

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    Prediction of Fatigue Crack Growth in Metal Materials via Spatiotemporal Neural Network
    LIANG Jiaming, YU Yin, HU Yile
    Journal of Shanghai Jiao Tong University    2026, 60 (3): 511-521.   DOI: 10.16183/j.cnki.jsjtu.2024.090
    Abstract796)   HTML23)    PDF(pc) (30162KB)(1130)       Save

    An image-driven model based on spatiotemporal neural network (STNN) is proposed for prediction of crack growth in aluminum alloy. Fatigue experiments with an initial edge crack angle of 0° and a 15.0% limit load level are designed, and images of specimen deformation are captured using digital image correlation (DIC) resulting in 5 511 frames of displacement field data used as datasets of STNN after interpolation, augmentation, and dimension-raising. Two neural netwroks, convolutional long short-term memory (Conv-LSTM) and SimVP, are employed to predict the fatigue crack growth, with their prediction accuracies further compared based on the structural similarity index measure (SSIM) and the root mean square error (RMSE). The results show that the SimVP neural network performs better in the test stage predicting fatigue crack growth rate and propagation path. This method provides a reference for damage tolerance analysis and determination of inspection intervals for structures.

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    Modeling Methods for Power Secondary System Simulation in New Power Systems
    HE Ruiwen, XIE Haijun, LU Jialiang, YANG Changxin, MOHAMMAD Shahidehpour
    Journal of Shanghai Jiao Tong University    2025, 59 (11): 1581-1591.   DOI: 10.16183/j.cnki.jsjtu.2023.556
    Abstract1949)   HTML31)    PDF(pc) (2421KB)(1009)       Save

    New power system achitecture will greatly increase the difficulty and vulnerability of the operation and control of power systems. The high integration of information and communication technology (ICT) promotes comprehensive information sharing, but it also highlights the urgency of establishing modeling and analysis methods for ICT-based power secondary systems. In this paper, simulation modeling methods for power secondary systems are proposed for the first time to achieve information sharing under interconnectivity and interoperability criteria. A smart substation secondary system with complex functional descriptions is taken as the research object. First, a structural model of intelligent electronic devices (IEDs) is proposed which meets the interconnectivity requirements. Then, a functional model of IEDs with built-in algorithms for secondary business in power systems is proposed, as well as power communication protocol models which meet the interoperability requirements under IEC 61850 standard. Furthermore, the IED function in the node domain and data exchange between IEDs in the network domain are achieved, through the state design in the process domain. Finally, taking a typical 220 kV substation line current protection as an example, the entire process of protection setting modification and protection actions after a fault occurs are simulated by correlating the operating status of the power primary system, verifying the correctness of the proposed simulation models.

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    Optimization of Geometrical Parameters of Coandă-Effect-Based Polymetallic Nodule Collection Device
    ZHANG Baiyuan, ZHAO Guocheng, XIAO Longfei
    Journal of Shanghai Jiao Tong University    2025, 59 (8): 1059-1066.   DOI: 10.16183/j.cnki.jsjtu.2023.470
    Abstract2987)   HTML38)    PDF(pc) (3985KB)(990)       Save

    The collection of seabed ore particles is a core technology of exploiting deep sea mineral resources, with wall-attached jet collection technology based on Coandă-effect being considered as a nodule collection method with engineering application potential. Based on the experimentally verified CFD-DEM numerical simulation, the optimization of geometric parameters of the collection device is conducted to improve pick-up efficiency. The influences of three geometric parameters, i.e., the ratio of the curvature radius of the convex curved wall to the diameter of the nodule particle R/d, the tangential radian of the jet θ, and the ratio of the thickness of the jet to the diameter of the nodule b/d on the critical unconditional jet flow rate q0, are investigated and compared. The nodule collection characteristics are revealed through an analysis of the flow field characteristics. The results show that b/d has the greatest influence on the pick-up efficiency, followed by R/d, while θ has the least. The performance of nodule collection is optimal when R/d=9, θ=1.05 rad, and b/d=0.26 in contrast conditions. This research provides technical support for designing and developing the Coandă-effect-based collection devices.

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    Design and Motion Modeling of a Small-Scale Lunar Jumping Robot
    YAN He, ZHU Xingyue, HOU Zhangli, WANG Weijun, ZHANG Zhinan
    Journal of Shanghai Jiao Tong University    2025, 59 (8): 1169-1180.   DOI: 10.16183/j.cnki.jsjtu.2023.646
    Abstract1849)   HTML10)    PDF(pc) (10631KB)(980)       Save

    Jumping is a viable form of locomotion for lunar surface exploration. However, due to the limited research on the coupling between jumping robots and the lunar surface, applying jumping robots for lunar surface detection remains challenging. Aiming at the load index of 5 kPa for the lunar surface detector, a new energy storage leg configuration of a jumping robot was proposed to realize low load jump with variable initial velocity and direction during take-off. The parameters of energy storage element were optimized to realize near-constant force take-off of the robot, which was validated in a dynamic simulation environment. To enable accurate jumps on the surface of the moon, a lunar soil mechanical property model considering damping characteristics was proposed, a discrete element simulation environment was built to determine the mechanical parameters, with a jumping dynamics model of the lunar surface robot established to verify the model accuracy through discrete element dynamics coupling simulation. Based on this dynamic model, two motion planning algorithms are implemented, confirming the application of the model.

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    Junction Temperature Algorithm of IGBT for Interface Converter in Optical Storage Microgrid System Considering Three-Dimensional Transverse Heat Conduction
    XU Yang, XIAO Qian, JIA Hongjie, JIN Yu, MU Yunfei, LU Wenbiao
    Journal of Shanghai Jiao Tong University    2025, 59 (10): 1533-1545.   DOI: 10.16183/j.cnki.jsjtu.2023.577
    Abstract1847)   HTML6)    PDF(pc) (6989KB)(979)       Save

    It is difficult for the existing junction temperature algorithms of insulated gate bipolar transistor (IGBT) to evaluate the impact on the thermal diffusion angle of the IGBT module under varying output power and heat dissipation conditions of optical storage unit interface converters in optical storage microgrids, which results in limited accuracy of junction temperature algorithm and poses a huge challenge to system thermal management. To address the above issues, a junction temperature algorithm of IGBT in interface converters in optical storage microgrid systems is proposed considering three-dimensional transverse heat conduction (3-D THC). First, a physical thermal model of power devices is established considering the thermal coupling between multiple chips in the optical storage microgrid system. Then, a junction temperature algorithm considering 3-D THC is further proposed based on the established physical model, and a thermal network model considering 3-D THC is established, which effectively improves the calculation accuracy of current state thermal parameters and power module thermal diffusion angle. Finally, the accuracy of the proposed model is verified using finite element analysis in the PinFin heat sink structure. The simulation results show that compared with various junction temperature algorithms, the proposed algorithm has the smallest error in junction temperature calculation under steady-state and sudden power change conditions, with approximately 3.11% and 3.65% respectively, which increases accuracy by 11.53% and 61.93% respectively compared with the algorithm not considering thermal diffusion angle (α=0). The proposed algorithm also has the highest junction temperature accuracy and the smallest error under different heat dissipation conditions.

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    Applications and Prospects of Educational Robots in Higher Education
    ZHAN Haiying, LU Xiaofei
    Contemporary Foreign Languages Studies    2025, 25 (4): 109-121.   DOI: 10.3969/j.issn.1674-8921.2025.04.010
    Abstract355)   HTML9)    PDF(pc) (1346KB)(976)       Save

    With the rapid development of educational robotics technology, numerous empirical studies have explored its applications in higher education. This paper provides a systematic review of 41 empirical studies on the use of educational robots in higher education, analyzing them from five dimensions: the distribution of academic disciplines;the types, functions, and roles of robots in educational settings;the purpose of robot applications;the types of data collected and the reported effects of robot applications;and the identified issues and challenges. The analysis revealed five major academic disciplines, four types of robots, three application roles, four application purposes, five types of research data, four aspects of application effects, and three categories of issues and challenges across the studies reviewed. Based on these findings, this paper further explores the prospects of educational robots in higher education, with the aim to provide directional guidance for future research and practice.

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    Interpretation of the 2025 American Society for Gastrointestinal Endoscopy guideline on diagnosis and management of GERD
    SANG Huaiming, WU Gaojue, TANG Yurong
    Journal of Surgery Concepts & Practice    2025, 30 (05): 385-391.   DOI: 10.16139/j.1007-9610.2025.05.03
    Abstract297)   HTML40)    PDF(pc) (1002KB)(976)       Save

    Released in February 2025, American Society for Gastrointestinal Endoscopy(ASGE) guideline on the diagnosis and management of gastroesophageal reflux disease(GERD), is based on a large body of evidence-based medical evidence over the past decade. It has systematically updated the indications for endoscopic examination, standards for high-quality endoscopic examination, and multidimensional management strategies, while focusing on elucidating the new role of endoscopic intervention in the diagnosis and treatment of GERD. The guideline aimed to provide clinicians with an authoritative guiding tool that integrates both scientific and practical value.

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    The Impact of GenAI-Instructor Collaborative Feedback on Learner Engagement and Revision Quality: An Empirical Study Based on Literary Translation Post-Editing
    LV Qianxi, JIANG Zhaokun
    Contemporary Foreign Languages Studies    2025, 25 (5): 156-169.   DOI: 10.3969/j.issn.1674-8921.2025.05.016
    Abstract346)   HTML10)    PDF(pc) (5065KB)(973)       Save

    The integration of GenAI into translation training is calling for the optimization of feedback mechanisms to enhance learner engagement. This study investigates the influence of feedback modality (GenAI-only feedback vs. GenAI-instructor collaborative feedback) and feedback complexity on learners’ emotional, cognitive, and behavioral engagement, as well as on the quality of subsequent revisions. Twenty-four senior undergraduate students completed a literary MTPE task incorporating typical rhetorical devices. Data were obtained from their revised outputs, questionnaire responses, and semi-structured interviews. Our findings reveal that: (1) collaborative feedback significantly enhanced three dimensions of engagement and revision quality; (2) learners favored concise and contextually relevant feedback, indicating that feedback complexity should be dynamically tailored to task characteristics and individual learner profiles; and (3) the interaction between emotional and cognitive engagement facilitated more effective revisions. Overall, collaborative feedback demonstrated superior credibility, comprehensibility, and actionability compared to GenAI-only feedback, thereby fostering learner engagement more effectively. This research offers empirical evidence for refining feedback mechanisms in MTPE instruction in the era of AI and provides practical insights for the design of intelligent, human—machine collaborative educational strategies.

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    Investigation on Steady-State Thermal Performance of Gear Box Based on Thermal-Fluid-Solid Coupling
    LIU Yi, ZHANG Kailin, SHAO Shuai, XIANG Hongxu
    Journal of Shanghai Jiao Tong University    2025, 59 (5): 666-674.   DOI: 10.16183/j.cnki.jsjtu.2023.225
    Abstract1905)   HTML7)    PDF(pc) (16774KB)(971)       Save

    In order to accurately predict the temperature distribution of the gearbox of the rail transit transmission system, a mixed timescale coupling method based on computational fluid dynamics (CFD) was adopted to simulate the gearbox. The internal flow field and temperature field of the gearbox were simultaneously simulated, and the real-time two-way coupling between the flow field and temperature field was realized through data transmission. Finally, based on the calculation results of the internal temperature field, the temperature distribution of the gearbox was obtained by using the finite element method. In addition, the effects of rotational speed, immersion depth, injection lubrication, and other factors on the steady-state thermal performance of the gearbox were analyzed. The results show that the numerical model has a good performance in temperature prediction. Moreover, the maximum relative error between the simulation results and the experimental values is 7.4%. With the increase of rotational speed, the temperature of gear box rises accordingly. With the increase of oil immersion depth, except the fact that the bottom temperature of the lower box gradually increases, the temperature of other areas decreases. At the same speed, the maximum temperature of the box under oil injection lubrication can be reduced by up to 14% compared with splash lubrication. In addition, the rotational speed increases, the cooling effect becomes more apparent.

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    Experimental Study on Vortex-Induced Vibration Force Characteristics of Side-by-Side Double Free-Hanging Water Transmission Pipes Under Uniform Flow
    ZHAO Guangyi, ZHANG Mengmeng, FU Shixiao, XU Yuwang, REN Haojie, BAI Yingli
    Journal of Shanghai Jiao Tong University    2025, 59 (8): 1067-1080.   DOI: 10.16183/j.cnki.jsjtu.2023.539
    Abstract2746)   HTML15)    PDF(pc) (32003KB)(965)       Save

    This paper investigates vortex-induced vibration (VIV) characteristics of double free-hanging water transmission pipes, which are crucial for temperature difference energy harvesting platforms. Compared to a single pipe, double pipes could offer higher transport efficiency and cost-effectiveness. In this paper, model experiments were conducted to analyze VIV characteristics of the double free-hanging pipes and a method for identifying vortex-induced loads for large displacements and small deformations was proposed. A comparative analysis of the VIV characteristics of double free-hanging pipe and the single pipe was performed. The findings show that VIV displacement amplitudes of double free-hanging pipe are similar at low flow velocities but differ with those of single pipe at high velocities. The double free-hanging pipe is more prone to instability in VIV, including traveling waves and multi-frequency responses. The VIV frequencies of double free-hanging pipe can be predicted by the same Strouhal number as that of the single pipe. Additionally, a significant difference in the added mass coefficient affects natural wet frequency adjustment for VIV resonance.

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